For this activity I have to read two online stories about the use of big datasets.
Duhigg (2012) How companies learn your secrets
- each shopper was assigned a unique code that kept tabs on everything bought
- demographic information was linked to the code
- additional data about ethnicity, job history etc was bought to add to the shopper’s profile
- predictive analytics departments were being created and statisticians were in demand
- behavioural research was used
- privacy laws had to be adhered to or else customers would become uncomfortable about how the company knew particular things about them.
Mangalindan (2012) Amazon’s recommendation secrets
- Amazon know more about their customers then Facebook or Google.
- Use information related to past purchases, items rated/liked and what other customers have also viewed and purchased.
- ‘item-to-item collaborative filtering’
- Amazon also use employees to market specific products email offers are filtered to decrease the number of emails sent
- now using Add-ons for cheaper products – customers are likely to add to their shopping as its only a few pounds more- similar to supermarket special offers
Extending my reading to search for “big data” through google and looking at a larger company – Starbucks.
“Starbucks knows how you like your coffee” Whitten (2016)
Reason for using big data:
- Consumer data was collected to help develop Starbuck’s new line of products
- Also used data from several consumer research firms to help with production of new grocery product lines
- Culled at-home information about consumption of their product.
Who benefited from it’s use?
- Starbucks and their stakeholders/investors
- Consumers – got new range of products
What the benefits were:
- Smart marketing approach allowed Starbucks to move into grocery products
- Starbucks brand was expanded through creation of K-Cups and bottled beverages and consumption was doubled
- Using consumer preference gets consumers to avoid other products while shopping/at home.
My reactions to the use of my data
- Can help reduce searches made while shopping or researching
- Can help develop/produce/improve products to meet my needs
- encourages over spending when alternatives shown or shared through other people’s buying
- encourages contact from 3rd parties
- details can be sold on without consent (small print or box tick missed)
- Don’t like knowing just how far my details are being used by companies to benefit them
- It’s not just ‘Big Brother’ watching everything I do online.
Duhigg, C (2012) ‘How companies learn from your secrets’, New York Times Magazine, 16 February, [online] available at http://www.nytimes.com/2012/02/19/magazine/shopping-habits.html?pagewanted=all&_r=0 (accessed 03 July 2016).
Mangalindon, J. P., (2012) ‘ Amazon’s recommendation secret’, Fortune, 30 July, 11:09 am EDT [online] available at http://fortune.com/2012/07/30/amazons-recommendation-secret/ (accessed 03 July 2016)
Whitten, S. (2016) ‘Starbucks knows how you like your coffee’, CNBC, 6 April, 2.37 pm ET [online] available at http://www.cnbc.com/2016/04/06/ (accessed on 03 July 2016)